{"id":503,"date":"2024-01-10T16:07:34","date_gmt":"2024-01-10T16:07:34","guid":{"rendered":"https:\/\/physicaldb.ece.ufl.edu\/?page_id=503"},"modified":"2026-11-07T14:22:12","modified_gmt":"2026-11-07T14:22:12","slug":"datasets-2","status":"publish","type":"page","link":"https:\/\/physicaldb.ece.ufl.edu\/index.php\/datasets-2\/","title":{"rendered":"Physical Datasets"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"503\" class=\"elementor elementor-503\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4c5c12b e-flex e-con-boxed e-con e-parent\" data-id=\"4c5c12b\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-cb45c93 e-con-full e-flex e-con e-child\" data-id=\"cb45c93\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-01f18b0 elementor-widget elementor-widget-text-editor\" data-id=\"01f18b0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h1>Overview<\/h1>\n\n<p style=\"font-size:20px\">With the rapid advancement of technology, artificial intelligence (AI) and machine learning (ML) have emerged as key drivers of automation, progressively taking over roles traditionally filled by manual inspection methods. Central to this technological revolution is the need for comprehensive datasets, derived from diverse sources like X-ray, SEM (Scanning Electron Microscopy), THz (Terahertz) imaging, acoustic, optical, thermal analysis, and meticulous sample preparation. These datasets are the cornerstone for developing advanced algorithms that are reshaping the future of electronic systems. This scarcity of resources is a significant barrier, hindering innovation and collaborative efforts in the electronic systems sector. Recognizing this crucial need, Physical DB is committed to providing a secure, accessible platform for the sharing and utilization of these essential datasets. Our platform transcends being a mere collection of datasets; it is an active, thriving ecosystem aimed at engaging and empowering professionals across various domains &#8211; researchers, engineers, and industry experts alike. We strive to democratize access to these valuable resources, creating a centralized hub for data sharing that nurtures a spirit of collaboration and community.\n<\/p>\n\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-b6768af e-con-full e-flex e-con e-parent\" data-id=\"b6768af\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-13e9d80 elementor-widget__width-initial elementor-widget elementor-widget-html\" data-id=\"13e9d80\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"header\">\r\n  <h2>Optical Imaging<\/h2>\r\n<\/div>\r\n\r\n<div class=\"container\">\r\n  <div class=\"card\">\r\n    <table class=\"card-table\" style=\"width: 100%;\">\r\n      <tr>\r\n        <td>\r\n          <div class=\"card-content\">\r\n            <div style=\"display: flex; align-items: center;\">\r\n              <img decoding=\"async\" src=\"https:\/\/physicaldb.ece.ufl.edu\/wp-content\/uploads\/2024\/01\/download.png\" alt=\"FPIC logo\"\r\n                style=\"width: auto; height: 50px; margin-right: 10px;\">\r\n              <h3 style=\"margin: 0; font-size: 24px;\">\r\n                <a style=\"color:black;\" href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/fics-pcb-image-collection-fpic\/\" target=\"_blank\" rel=\"noopener\">\r\n                  FPIC\r\n                <\/a>\r\n              <\/h3>\r\n            <\/div>\r\n            <p style=\"font-size:25px\">\r\n              The FPIC dataset was introduced to meet the growing demand for labeled ground truth data in the outsourced PCB manufacturing and hardware assurance sectors.\r\n              <a href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/fics-pcb-image-collection-fpic\/\" target=\"_blank\" rel=\"noopener\"> read more...<\/a>\r\n            <\/p>\r\n            <div class=\"card-info\">\r\n              <ul style=\"list-style-type: none; display: flex;\">\r\n                <li>&bull; PCB Assurance<\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull; 71,000 annotated instances<\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull; 261 images of 93 separate PCBs<\/li>\r\n              <\/ul>\r\n            <\/div>\r\n          <\/div>\r\n        <\/td>\r\n      <\/tr>        \r\n      <tr>\r\n        <td>\r\n          <div class=\"card-content\">\r\n            <div style=\"display: flex; align-items: center;\">\r\n              <img decoding=\"async\" src=\"https:\/\/physicaldb.ece.ufl.edu\/wp-content\/uploads\/2024\/01\/download.png\" alt=\"\"\r\n                style=\"width: auto; height: 50px; margin-right: 10px;\">\r\n              <h3 style=\"margin: 0; font-size: 24px;\"><a style=\"color:black;\"\r\n                  href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/logo-classification\/\">Logo Classification<\/a><\/h3>\r\n            <\/div>\r\n            <p style=\"font-size:25px\">This study examines various methods for automating the recognition and\r\n              categorization of logos found on printed circuit boards (PCBs) and integrated circuits (ICs).\r\n              <a href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/logo-classification\/\" target=\"_blank\"> read more...<\/a>\r\n            <\/p>\r\n            <div class=\"card-info\">\r\n\r\n              <ul style=\"list-style-type: none; display: flex;\">\r\n                <li>&bull;logos on PCBs and ICs<\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull;18 classes<\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull;>14,000 images <\/li>\r\n              <\/ul>\r\n\r\n            <\/div>\r\n          <\/div>\r\n        <\/td>\r\n      <\/tr>\r\n      <tr>\r\n        <td>\r\n          <div class=\"card-content\">\r\n            <div style=\"display: flex; align-items: center;\">\r\n              <img decoding=\"async\" src=\"https:\/\/physicaldb.ece.ufl.edu\/wp-content\/uploads\/2024\/01\/download.png\" alt=\"DeepIC Logo\"\r\n                style=\"width: auto; height: 50px; margin-right: 10px;\">\r\n              <h3 style=\"margin: 0; font-size: 24px;\"><a style=\"color:black\"\r\n                  href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/elementor-425\/\">Text Recognition For PCBs<\/a><\/h3>\r\n            <\/div>\r\n            <p style=\"font-size:25px\">The document titled \"Deep Learning-Based Approaches for Text Recognition in\r\n              PCB Optical Inspection\": A Survey\r\n              <a href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/elementor-425\/\" target=\"_blank\"> read more...<\/a>\r\n            <\/p>\r\n            <div class=\"card-info\">\r\n              <ul style=\"list-style-type: none; display: flex;\">\r\n                <li>&bull;34 high-resolution pcb images used<\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull;6,089 component markings and reference designators\r\n\r\n                <\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull;The annotations are in the ICDAR format. <\/li>&nbsp;&nbsp;&nbsp;\r\n\r\n              <\/ul>\r\n\r\n            <\/div>\r\n          <\/div>\r\n        <\/td>\r\n      <\/tr>\r\n      <tr>\r\n        <td>\r\n          <div class=\"card-content\">\r\n            <div style=\"display: flex; align-items: center;\">\r\n              <img decoding=\"async\" src=\"https:\/\/physicaldb.ece.ufl.edu\/wp-content\/uploads\/2024\/01\/download.png\" alt=\"DeepIC Logo\"\r\n                style=\"width: auto; height: 50px; margin-right: 10px;\">\r\n              <h3 style=\"margin: 0; font-size: 24px;\"><a style=\"color:black;\"\r\n                  href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/elementor-430\/\">IC-SynthLogo Dataset<\/a><\/h3>\r\n            <\/div>\r\n            <p style=\"font-size:25px\">The IC SynthLogo dataset is a synthetic image dataset created to enhance the\r\n              detection of counterfeit and recycled Integrated Circuits (ICs)\r\n              in Printed Circuit Boards (PCBs). It utilizes\r\n              <a href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/elementor-430\/\" target=\"_blank\"> read more...<\/a>\r\n            <\/p>\r\n            <div class=\"card-info\">\r\n              <ul style=\"list-style-type: none; display: flex;\">\r\n                <li>&bull;826 number of logos<\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull;188 number of regions to implant<\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull;28436 synthetic images<\/li>\r\n              <\/ul>\r\n\r\n            <\/div>\r\n          <\/div>\r\n        <\/td>\r\n      <\/tr>\r\n      <tr>\r\n        <td>\r\n          <div class=\"card-content\">\r\n            <div style=\"display: flex; align-items: center;\">\r\n              <img decoding=\"async\" src=\"https:\/\/physicaldb.ece.ufl.edu\/wp-content\/uploads\/2024\/01\/download.png\" alt=\"DeepIC Logo\"\r\n                style=\"width: auto; height: 50px; margin-right: 10px;\">\r\n              <h3 style=\"margin: 0; font-size: 24px;\"><a style=\"color:black;\"\r\n                  href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/elementor-420\/\" target=\"_blank\"> EC-SEG: Electronic\r\n                  Component Segmentation<\/a><\/h3>\r\n            <\/div>\r\n            <p style=\"font-size:25px\">The document \"EC-Seg: Electronic Component Segmentation for PCB Assurance and\r\n              Counterfeit Avoidance\"\r\n              presents a study focused on enhancing PCB assurance through an automated\r\n              <a href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/elementor-420\/\" target=\"_blank\"> read more...<\/a>\r\n            <\/p>\r\n            <div class=\"card-info\">\r\n              <ul style=\"list-style-type: none; display: flex;\">\r\n                <li>&bull;Component segmentation and localization<\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull;sensor fusion <\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull;BoM extraction <\/li>\r\n              <\/ul>\r\n\r\n            <\/div>\r\n          <\/div>\r\n        <\/td>\r\n      <\/tr>\r\n      <tr>\r\n        <td>\r\n          <div class=\"card-content\">\r\n            <div style=\"display: flex; align-items: center;\">\r\n              <img decoding=\"async\" src=\"https:\/\/physicaldb.ece.ufl.edu\/wp-content\/uploads\/2024\/01\/download.png\" alt=\"DeepIC Logo\"\r\n                style=\"width: auto; height: 50px; margin-right: 10px;\">\r\n              <h3 style=\"margin: 0; font-size: 24px;\"><a style=\"color:black\"\r\n                  href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/deeplogoic\/\" target=\"_blank\"> DeepIC Logo<\/a><\/h3>\r\n            <\/div>\r\n            <p style=\"font-size:25px\">The DeepIC Logo dataset detailed emerges a crucial response to the growing\r\n              hardware\r\n              challenges caused by undetected faults in printed circuit board (PCB)\r\n              <a href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/deeplogoic\/\" target=\"_blank\"> read more...<\/a>\r\n            <\/p>\r\n            <div class=\"card-info\">\r\n              <ul style=\"list-style-type: none; display: flex;\">\r\n                <li>&bull;1010 logo instances<\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull;980 sample images<\/li>&nbsp;&nbsp;&nbsp;\r\n                <li>&bull;119 classes <\/li>\r\n              <\/ul>\r\n\r\n            <\/div>\r\n\r\n          <\/div>\r\n        <\/td>\r\n      <\/tr>\r\n\r\n    <\/table>\r\n  <\/div>\r\n<\/div>\r\n\r\n<\/body>\r\n\r\n<\/html>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-f421ecb e-con-full e-flex e-con e-parent\" data-id=\"f421ecb\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-55d8433 elementor-widget__width-initial elementor-widget elementor-widget-html\" data-id=\"55d8433\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<!DOCTYPE html>\r\n<html lang=\"en\">\r\n<head>\r\n<meta charset=\"UTF-8\">\r\n<meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\">\r\n<title> Datasets<\/title>\r\n<style>\r\n  body {\r\n    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;\r\n    margin: 0;\r\n    padding: 0;\r\n  }\r\n  .header {\r\n    background: #66B2B2;\r\n    padding: 10px 40px;\r\n    color: white;\r\n    text-shadow: 1px 1px #333;\r\n  }\r\n  .header h2 {\r\n    margin: 0;\r\n    padding: 10px 0;\r\n  }\r\n  .container {\r\n    display: flex;\r\n    flex-wrap: wrap;\r\n    justify-content: center;\r\n    padding: 20px;\r\n  }\r\n  .card {\r\n    background: white;\r\n    border-radius: 1px;\r\n    box-shadow: 0 4px 8px rgba(0,0,0,0.1);\r\n    margin: 10px;\r\n    overflow: hidden;\r\n    transition: transform 0.3s ease-in-out;\r\n    width: calc(100% - 20px);\r\n    display: flex;\r\n    flex-direction: column;\r\n    align-items: flex-start;\r\n  }\r\n  .card:hover {\r\n    transform: translateY(-5px);\r\n  }\r\n  .card-content {\r\n    padding: 20px 20;\r\n  }\r\n  .card-info {\r\n    padding: 0 20px 20px 20px;\r\n    width: 100%;\r\n    display: flex; \r\n    font-size: 22px;\r\n  }\r\n  .card-info div {\r\n    margin-right: 15px; \/* Adds spacing between the info divs *\/\r\n  }\r\n  .card-table td {\r\n    padding-bottom: 20px; \/* Add padding to the bottom of each cell *\/\r\n  }\r\n  .card-table td:first-child {\r\n    border-bottom: 2px solid #ccc; \/* Add border to separate the rows *\/\r\n  }\r\n  @media (max-width: 768px) {\r\n    .card {\r\n      width: calc(110% - 20px);\r\n    }\r\n  }\r\n<\/style>\r\n<\/head>\r\n<body>\r\n\r\n<div class=\"header\">\r\n  <h2>SEM Imaging<\/h2>\r\n<\/div>\r\n\r\n<div class=\"container\">\r\n  <div class=\"card\">\r\n    <table class=\"card-table\" style=\"width: 100%;\">\r\n      <tr>\r\n        <td>\r\n          <div class=\"card-content\">\r\n            <div style=\"display: flex; align-items: center;\">\r\n              <img decoding=\"async\" src=\"https:\/\/physicaldb.ece.ufl.edu\/wp-content\/uploads\/2024\/01\/download.png\" alt=\"DeepIC Logo\" \r\n              style=\"width: auto; height: 50px; margin-right: 10px;\">\r\n              <h3 style=\"margin: 0; font-size: 24px;\"><a style=\"color:black;\" href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/ic-cell-image-dataset-using-sem-imaging\/\" target=\"_blank\">IC Cell Image Dataset using SEM Imaging<\/a><\/h3>\r\n            <\/div>\r\n            <p style=\"font-size:25px\">The \"Explainable Vision System for Hardware Testing and Assurance\" (EVHA) is a novel system developed for enhancing the security\r\n            <a href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/ic-cell-image-dataset-using-sem-imaging\/\" target=\"_blank\"> read more..<\/a>\r\n          <\/p>\r\n            <div class=\"card-info\">\r\n              <p>&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp <\/p>\r\n              \r\n<ul style=\"list-style-type: none; display: flex;\">\r\n  <li>&bull;(CMOS) technology node\r\n<\/li>&nbsp;&nbsp;&nbsp;\r\n  <li>&bull;115 images<\/li>&nbsp;&nbsp;&nbsp;\r\n  <li>&bull;3 dwelling times <\/li>\r\n<\/ul>\r\n\r\n            <\/div>\r\n          <\/div>\r\n        <\/td>\r\n      <\/tr>\r\n      \r\n    <\/table>\r\n  <\/div>\r\n<\/div>\r\n\r\n<\/body>\r\n<\/html>\r\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-e182d1b e-con-full e-flex e-con e-parent\" data-id=\"e182d1b\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f341a8e elementor-widget__width-initial elementor-widget elementor-widget-html\" data-id=\"f341a8e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<!DOCTYPE html>\r\n<html lang=\"en\">\r\n<head>\r\n<meta charset=\"UTF-8\">\r\n<meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\">\r\n<title> Datasets<\/title>\r\n<style>\r\n  body {\r\n    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;\r\n    margin: 0;\r\n    padding: 0;\r\n  }\r\n  .header {\r\n    background: #66B2B2;\r\n    padding: 10px 40px;\r\n    color: white;\r\n    text-shadow: 1px 1px #333;\r\n  }\r\n  .header h2 {\r\n    margin: 0;\r\n    padding: 10px 0;\r\n  }\r\n  .container {\r\n    display: flex;\r\n    flex-wrap: wrap;\r\n    justify-content: center;\r\n    padding: 20px;\r\n  }\r\n  .card {\r\n    background: white;\r\n    border-radius: 1px;\r\n    box-shadow: 0 4px 8px rgba(0,0,0,0.1);\r\n    margin: 10px;\r\n    overflow: hidden;\r\n    transition: transform 0.3s ease-in-out;\r\n    width: calc(100% - 20px);\r\n    display: flex;\r\n    flex-direction: column;\r\n    align-items: flex-start;\r\n  }\r\n  .card:hover {\r\n    transform: translateY(-5px);\r\n  }\r\n  .card-content {\r\n    padding: 20px 20;\r\n  }\r\n  .card-info {\r\n    padding: 0 20px 20px 20px;\r\n    width: 100%;\r\n    display: flex; \r\n    font-size: 22px;\r\n  }\r\n  .card-info div {\r\n    margin-right: 15px; \/* Adds spacing between the info divs *\/\r\n  }\r\n  .card-table td {\r\n    padding-bottom: 20px; \/* Add padding to the bottom of each cell *\/\r\n  }\r\n  .card-table td:first-child {\r\n    border-bottom: 2px solid #ccc; \/* Add border to separate the rows *\/\r\n  }\r\n  @media (max-width: 768px) {\r\n    .card {\r\n      width: calc(110% - 20px);\r\n    }\r\n  }\r\n<\/style>\r\n<\/head>\r\n<body>\r\n\r\n<div class=\"header\">\r\n  <h2>Xray Imaging<\/h2>\r\n<\/div>\r\n\r\n<div class=\"container\">\r\n  <div class=\"card\">\r\n    <table class=\"card-table\" style=\"width: 100%;\">\r\n      <tr>\r\n        <td>\r\n          <div class=\"card-content\">\r\n            <div style=\"display: flex; align-items: center;\">\r\n              <img decoding=\"async\" src=\"https:\/\/physicaldb.ece.ufl.edu\/wp-content\/uploads\/2024\/01\/download.png\" alt=\"DeepIC Logo\" \r\n              style=\"width: auto; height: 50px; margin-right: 10px;\">\r\n              <h3 style=\"margin: 0; font-size: 24px;\"><a style=\"color:black;\" href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/pcb-x-ray-raw-data-collection\/\" target=\"_blank\">PCB X-ray Raw Data Collection<\/a><\/h3>\r\n            <\/div>\r\n            <p style=\"font-size:25px\">The document titled \"FICS PCB X-ray: A dataset for automated printed circuit board inter-layers inspection\" outlines a significant \r\n            <a href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/pcb-x-ray-raw-data-collection\/\" target=\"_blank\"> read more...<\/a>\r\n          <\/p>\r\n            <div class=\"card-info\">\r\n              <ul style=\"list-style-type: none; display: flex;\">\r\n                  <li>&bull;5 PCB samples<\/li>&nbsp;&nbsp;&nbsp;\r\n  <li>&bull;16-bit Tiff files<\/li>&nbsp;&nbsp;&nbsp;\r\n  <li>&bull;annotated X-ray layer images<\/li>&nbsp;&nbsp;&nbsp;\r\n  <li>&bull;X-ray data of PCBs <\/li>\r\n<\/ul>\r\n\r\n            <\/div>\r\n          <\/div>\r\n        <\/td>\r\n      <\/tr>\r\n      <tr>\r\n        <td>\r\n          <div class=\"card-content\">\r\n            <div style=\"display: flex; align-items: center;\">\r\n              <img decoding=\"async\" src=\"https:\/\/physicaldb.ece.ufl.edu\/wp-content\/uploads\/2024\/01\/download.png\" alt=\"DeepIC Logo\" \r\n              style=\"width: auto; height: 50px; margin-right: 10px;\">\r\n              <h3 style=\"margin: 0; font-size: 24px;\"><a style=\"color:black;\"href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/pcb-x-ray-ct-ground-truth-dataset\/\" target=\"_blank\">PCB X-ray CT Ground Truth Dataset<\/a><\/h3>\r\n            <\/div>\r\n            <p style=\"font-size:25px\">The \"PCB X-ray CT Ground Truth Dataset\" in the document is a unique and valuable resource for the development and testing of automated\r\n            <a href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/pcb-x-ray-ct-ground-truth-dataset\/\" target=\"_blank\"> read more...<\/a>\r\n          <\/p>\r\n            <div class=\"card-info\">\r\n              <ul style=\"list-style-type: none; display: flex;\">\r\n  <li>&bull;2D X-ray data from 360 degrees\r\n<\/li>&nbsp;&nbsp;&nbsp;\r\n  <li>&bull;Converted 16bit Tif to 8-bit JPG<\/li>&nbsp;&nbsp;&nbsp;\r\n  <li>&bull;486 to 1920 Tiff Stack images<\/li>\r\n  &nbsp;&nbsp;&nbsp;\r\n  <li>&bull;\r\n  PCB annotations vary (PCB1: 164 vias, 55 traces, 29 pads)<\/li>\r\n<\/ul>\r\n\r\n            <\/div>\r\n          <\/div>\r\n        <\/td>\r\n      <\/tr>\r\n      <tr>\r\n        <td>\r\n          <div class=\"card-content\">\r\n            <div style=\"display: flex; align-items: center;\">\r\n              <img decoding=\"async\" src=\"https:\/\/physicaldb.ece.ufl.edu\/wp-content\/uploads\/2024\/01\/download.png\" alt=\"DeepIC Logo\" \r\n              style=\"width: auto; height: 50px; margin-right: 10px;\">\r\n              <h3 style=\"margin: 0; font-size: 24px;\"><a style=\"color:black;\"href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/segpcbx-dataset\/\" target=\"_blank\">SegPCBX Dataset<\/a><\/h3>\r\n            <\/div>\r\n            <p style=\"font-size:25px\">The SegPCBX dataset encompasses 2D reconstructed X-ray images derived from the most optimized X-ray scan, offering extensive research opportunities  \r\n            <a href=\"https:\/\/physicaldb.ece.ufl.edu\/index.php\/segpcbx-dataset\/\" target=\"_blank\"> read more...<\/a>\r\n          <\/p>\r\n            <div class=\"card-info\">\r\n              <ul style=\"list-style-type: none; display: flex;\">\r\n  <li>&bull;COCO JSON format<\/li>&nbsp;&nbsp;&nbsp;\r\n  <li>&bull;400 annotated components<\/li>&nbsp;&nbsp;&nbsp;\r\n  <li>&bull;140 vias, 132 solder balls, 62 pads, 71 traces, and 2 copper planes<\/li>&nbsp;&nbsp;&nbsp;\r\n<\/ul>\r\n\r\n            <\/div>\r\n          <\/div>\r\n        <\/td>\r\n      <\/tr>\r\n    <\/table>\r\n  <\/div>\r\n<\/div>\r\n\r\n<\/body>\r\n<\/html>\r\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-f94e6d7 e-flex e-con-boxed e-con e-parent\" data-id=\"f94e6d7\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f71b8c4 elementor-widget elementor-widget-html\" data-id=\"f71b8c4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div style=\"background:#ffffff;border-top:2px solid #e5e7eb;padding:24px 28px;margin:24px 0;font-family:system-ui,-apple-system,'Segoe UI',Roboto,'Helvetica Neue',Arial,sans-serif;line-height:1.6;\">\r\n  <div style=\"font-size:16px;color:#111827;\">\r\n    This page is supported by Dr. Navid Asadi\u2019s research group at the University of Florida. For further information or collaboration opportunities, please contact <a href=\"mailto:nasadi@ufl.edu\" style=\"color:#4f46e5;text-decoration:none;\">nasadi@ufl.edu<\/a>.\r\n  <\/div>\r\n<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Overview With the rapid advancement of technology, artificial intelligence (AI) and machine learning (ML) have emerged as key drivers of automation, progressively taking over roles traditionally filled by manual inspection methods. Central to this technological revolution is the need for comprehensive datasets, derived from diverse sources like X-ray, SEM (Scanning Electron Microscopy), THz (Terahertz) imaging, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-503","page","type-page","status-publish","hentry"],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":8}},"_links":{"self":[{"href":"https:\/\/physicaldb.ece.ufl.edu\/index.php\/wp-json\/wp\/v2\/pages\/503","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/physicaldb.ece.ufl.edu\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/physicaldb.ece.ufl.edu\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/physicaldb.ece.ufl.edu\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/physicaldb.ece.ufl.edu\/index.php\/wp-json\/wp\/v2\/comments?post=503"}],"version-history":[{"count":86,"href":"https:\/\/physicaldb.ece.ufl.edu\/index.php\/wp-json\/wp\/v2\/pages\/503\/revisions"}],"predecessor-version":[{"id":1764,"href":"https:\/\/physicaldb.ece.ufl.edu\/index.php\/wp-json\/wp\/v2\/pages\/503\/revisions\/1764"}],"wp:attachment":[{"href":"https:\/\/physicaldb.ece.ufl.edu\/index.php\/wp-json\/wp\/v2\/media?parent=503"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}